Papers
1
Total Citations
28
H-Index
1
About
Xiaoqi Zhao is a rising researcher in multi-robot systems and autonomous navigation, with a focus on coverage path planning and artificial potential field methods. Their most cited work, "APF-CPP: An Artificial Potential Field Based Multi-Robot Online Coverage Path Planning Approach" (2024), introduces a novel framework that enhances real-time collaboration among robots for efficient area coverage tasks. By leveraging artificial potential fields, Zhao’s approach addresses key challenges in dynamic environments, enabling robots to adaptively coordinate without centralized control. This work has already garnered 28 citations, reflecting its timely impact on the field of swarm robotics and autonomous systems. Zhao’s contributions are particularly notable for their practical applicability in search-and-rescue, environmental monitoring, and industrial automation. Their research bridges theoretical advances in multi-agent coordination with real-world deployment, positioning them as an emerging voice in robotics. With a growing citation record and a focus on scalable, online solutions, Zhao is poised to influence next-generation autonomous systems. Their work continues to inspire students and researchers exploring decentralized multi-robot coordination and intelligent path planning.
Research Focus
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Top Papers
- 1